Bioinformatics Analysis of Genes and Signaling Pathways in Connection with the Pathogenesis of Bipolar Disorder

Bipolar disorder (BD), which also refers to manic-depressive disease, often synchronously develops accompanying mental disorder, endocrine, and long-term awful physical conditions and has a poor prognosis, making bipolar disorder a significant public health problem and a global disease burden. The disorder is highly heritable and has been shown to be genetically linked. Identifying and screening major molecular markers for therapeutic targeting has become a global concern. This paper aims to use a bioinformatics approach to screen genes included in the pathogenesis of bipolar affective disorder and to analyze their signaling pathways. In this study, mRNA expression profiles in the orbitofrontal cortex (GSE5389) and dorsolateral brain tissue (GSE5388) obtained from the GEO public database on the National Center for Biological Information (NCBI) website were employed in order to detect and analyze differentially expressed genes (DEGs) in the normal and disease groups adopting the limma package with the R language, followed by an application of Metascape database for GO and KEGG signaling pathway analysis and WGCNA package for GSE5389 for weighted gene co-expression network analysis in order to acquire the relevant modules as well as crucial genes relation. It was shown that patients with bipolar disorder, genes included in the development of neuronal cell development, cell agglutination, immune signaling, and glial cell regeneration are dysregulated.